@inproceedings{e2ef61e6622747ee9ade0a80ed2e9fa6,
title = "Traversability classification using super-voxel method in unstructured terrain",
abstract = "Estimating the traversability of terrain in an unstructured outdoor environment is one of the challenging issues in autonomous vehicles. When dealing with a large 3D point cloud, the computational cost of processing all of the individual points is very high. Thus voxelization methods are used extensively. In this paper, we propose a more fine-grained voxelization algorithm in the context of unstructured terrain classification. While the current shape of a voxel is a fixed-length cubic, we construct a flexible shape voxel which has spatial and geometrical properties. Furthermore, we propose a new shape histogram feature that represents the statistical characteristics of 3D points. The proposed method was tested using data obtained from unstructured outdoor environments for performance evaluation.",
keywords = "Point cloud, Traversability classification, Unmanned vehicle, Unstructured terrain, Voxel",
author = "Soohwan Song and Sungho Jo",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 3rd International Conference on Robot Intelligence Technology and Applications, RiTA 2014 ; Conference date: 06-11-2014 Through 08-11-2014",
year = "2015",
doi = "10.1007/978-3-319-16841-8_53",
language = "English",
isbn = "9783319168401",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "595--604",
editor = "Weimin Yang and Hyun Myung and Jong-Hwan Kim and Peter Sincak and Jun Jo",
booktitle = "Robot Intelligence Technology and Applications 3 - Edition of the Selected Papers from the 3rd International Conference on Robot Intelligence Technology and Applications",
address = "Germany",
}